A recent Gartner survey found that 47% of Chief Sales Officers (CSOs) rank increasing investments in artificial intelligence (AI) to improve seller effectiveness as a priority. However, few CSOs have reached the point of adopting or using AI or machine learning to positively affect their sales results.
This lack of adoption could be explained by option paralysis: Emerging technologies in AI are designed to transform sales models and cost structures, therefore making it difficult to assess where to invest. However, by 2024, Gartner expects 55% of B2B companies to employ AI to augment at least one of their primary sales processes. This is in line with previous Gartner data that found 72% of B2B buyers desire a “seller-free” sales experience.
To bridge the adoption gap, sales leaders must recognize that AI works best when used to support B2B sales reps in their daily sales tasks, such as lead prioritization or real-time customer insights. The technology also better enables empathy for sellers and improves customer engagement with hyper-personalization, resulting in better buyer engagement and improved revenue capture.
With this in mind, there are two key growth areas CSOs must prioritize their AI technology investments:
1. AI In Demand Generation
Sales leaders must first cleanse their customer relationship management (CRM) data to activate AI tools that automate digital marketing processes and enable chatbots and virtual customer assistants to serve real-time customer interactions. AI can also automate content distribution for buying tasks and help to personalize responses to convert more leads.
Suppliers that have already deployed predictive lead qualification, guided selling and AI-based opportunity scoring across their B2B sales organization will better understand and predict customer behavior. Additionally, this type of automation will help improve sales and marketing alignment for a continuous customer experience (CX).
2. AI In Forecasting
Sales forecasting continues to be an immediate opportunity for AI investment. For example, predictive forecasting solutions provide forecast indicators at the opportunity level that are used to help sellers determine if deals should be included or excluded from specific forecast categories.
Improvements in forecasting can improve efficiency in sales, help prioritize the right customers/deals to pursue and ultimately decrease the cost of sales and revenue acquisition. These savings can then be used to fund additional AI investments in sales and marketing.
Overall, the benefits of incorporating AI into sales organizations will vary by commercial function. On average, Gartner predicts that large, complex organizations using analytics, AI and automation in marketing capabilities will yield yearly benefits of $38.4 million in potential sales, while investing in sales management will yield $14.3 million in sales. Investing in sales enablement will yield $13.9 million, and sales processes rounds out the top four with $5 million.
Regardless of the function, CSOs who do not invest in AI are missing opportunities to increase efficiency and improve customer engagement.
Robert Blaisdell is a Sr. Director, Analyst in the Gartner Sales Research and Advisory Practice. He covers all aspects of sales but primarily focuses on current customer management and growth via account planning best practices and strategic key account management.
